###################################################### -*- mode: r -*- #####
## Scenario setup for Iterated Race (iRace).
############################################################################

## To use the default value of a parameter of iRace, simply do not set
## the parameter (comment it out in this file, and do not give any
## value on the command line).

## File that contains the description of the parameters.
parameterFile = "./parameters-NSGAII.txt"

## Directory where the programs will be run.
# execDir = "./"
execDir = "."

## File to save tuning results as an R dataset, either absolute path
## or relative to execDir.
# logFile = "./irace.Rdata"

## Directory where tuning instances are located, either absolute path or
## relative to current directory.
# trainInstancesDir = "./Instances"
trainInstancesDir = ""

## File with a list of instances and (optionally) parameters.
## If empty or NULL, do not use a file.
# trainInstancesFile = "instances-list.txt"
trainInstancesFile = "instances-list.txt"

## A file containing a list of initial configurations.
## If empty or NULL, do not use a file.
# configurationsFile = ""

## The script called for each configuration that launches the program to be
## tuned.  See templates/target-runner.tmpl
# targetRunner = "./target-runner"

## Number of times to retry a call to target-runner if the call failed.
# targetRunnerRetries = 0

## Optional data passed to targetRunner. This is ignored by the default
## targetRunner function, but it may be used by custom targetRunner functions
## to pass persistent data around.
# targetRunnerData = NULL

## Optional R function to provide custom parallelization of target.runner.  The
## signature of this function should be 'function(experiments, target.runner,
## scenario)', where target.runner is an R function, 'experiments' is a list
## such that each of its elements will be the argument to one call of
## target.runner, and scenario will also be passed to every call. See
## help(target.runner.default) for details.
# targetRunnerParallel = NULL

## Optional script that provides a numeric value for each configuration.
## See templates/target-evaluator.tmpl
# targetEvaluator = ""
# targetEvaluator = "./target-evaluator"

## The maximum number of runs (invocations of targetRunner) that will
## performed. It determines the (maximum) budget of experiments for the tuning.
# maxExperiments = 0
maxExperiments = 100000

## The maximum time in seconds for the runs of targetRunner that will be 
## performed. The mean execution time is estimated to calculate the maximum number 
## of experiments. When this is used targetRunner must return the execution time
## as second output.
# maxTime = 0             

## The percentage of the budget used for estimating the mean execution time.
## Only used when maxTime > 0.
# budgetEstimation = 0.02

## Directory where testing instances are located, either absolute or relative
## to current directory.
# testInstancesDir = ""

## File containing a list of test instances and optionally additional
## parameters for them.  If empty or NULL, do not use a file.
# testInstancesFile = ""
testInstancesFile = "" #TODO COMPLETA

## Number of elite configurations returned by irace that will be tested
## if test instances are provided.
# testNbElites = 1

## Enable/disable testing the elite configurations found at each iteration.
# testIterationElites = 0

## Indicates the number of decimal places to be considered for the
## real parameters.
# digits = 4

## A value of 0 silences all debug messages. Higher values provide
## more verbose debug messages.
# debugLevel = 0

## Number of iterations of Race. Do not use something else than the
## default (that is, the dynamic value) unless you know exactly what
## you are doing.
# nbIterations = 0

## Number of experiments per iteration. Do no use something else than
## the default (that is, the dynamic value) unless you know exactly
## what you are doing.
# nbExperimentsPerIteration = 0

## Sample the instances or take them always in the same order.
# sampleInstances = 1
sampleInstances = 0

## Specifies the statistical test type: F-test or t-test.
# testType = "F-test"

## Specifies how many instances are seen before the first elimination
## test. It must be a multiple of eachTest.
# firstTest = 5
firstTest = 9

## Specifies how many instances are seen between elimination tests.
# eachTest = 1
eachTest = 9

## The minimum number of configurations that should survive to continue one
## iteration. Do not use something else than the default (that is, the
## dynamic value) unless you know exactly what you are doing.
# minNbSurvival = 0

## The number of configurations that should be sampled and evaluated at
## each iteration. Do no use something else than
## the default (that is, the dynamic value) unless you know exactly
## what you are doing.
# nbConfigurations = 0

## This value is used to determine the number of configurations
## to be sampled and evaluated at each iteration. Use
## the default unless you know exactly what you are doing.
# mu = 5

## Enable/disable deterministic algorithm mode, if enabled irace
## will not use an instance more that once in each race. Note that
## if the number of instances provided is less than firstTest, no
## statistical test will be performed. 
# deterministic = 0

## Seed of the random number generator (must be a positive integer, NA
## means use a random seed).
# seed = NA

## Number of calls to targetRunner to execute in parallel. Less than 2
## means calls to targetRunner are sequentially executed.
#parallel = 0

## Enable/disable load-balancing when executing experiments in
## parallel. Load-balancing makes better use of computing resources, but
## increases communication overhead. If this overhead is large, disabling
## load-balancing may be faster.
# loadBalancing = 

## Specify how irace waits for jobs to finish when targetRunner submits jobs to
## a batch cluster: sge, pbs, torque or slurm (targetRunner must submit jobs to
## the cluster using. for example, qsub).
# batchmode = 0

## Enable/disable MPI. Use MPI to execute targetRunner in parallel
## (parameter parallel is the number of slaves).
# mpi = 0

## Enable/disable the soft restart strategy that avoids premature convergence
## of the probabilistic model.
# softRestart = 1

## Confidence level for the elimination test.
# confidence = 0.95

## Previously saved log file to recover the execution of irace, either
## absolute path or relative to the current directory. If empty or
## NULL, recovery is not performed.
# recoveryFile = ""

## File containing a list of logical expressions that cannot be true
## for any evaluated configuration. If empty or NULL, do not use a file.
# forbiddenFile = ""

## Enable/disable elitist irace.
# elitist = 1

## Number of instances to add to execution list before previous instances in
## elitist irace.
# elitistNewInstances  = 1

## Limit for the elitist race, number of statistical test performed without 
## elimination of configurations.
# elitistLimit  = 2

## END of scenario file
############################################################################
